import re

def check_ai_development_restrictions(code_text, tool_name="Claude Code"):
    """
    Check if code appears to be developing competing AI/ML systems
    that might violate terms of service for AI coding assistants.
    
    Args:
        code_text (str): The source code to analyze
        tool_name (str): Name of the AI coding tool being used
    
    Returns:
        dict: Analysis results with violation flags and warnings
    """
    
    # Keywords that indicate AI/ML system development
    ai_keywords = [
        'artificial intelligence', 'machine learning', 'large language model',
        'neural network', 'transformer', 'llm', 'ai model', 'training data',
        'fine-tuning', 'model architecture', 'embedding', 'tokenizer'
    ]
    
    # Competing product indicators
    competing_indicators = [
        'coding assistant', 'code completion', 'autocomplete',
        'intellisense', 'copilot', 'whisperer', 'ai assistant'
    ]
    
    violations = {
        'ai_development_detected': False,
        'competing_product_detected': False,
        'high_risk_patterns': [],
        'warning_message': ''
    }
    
    # Convert to lowercase for case-insensitive matching
    code_lower = code_text.lower()
    
    # Check for AI/ML development keywords
    ai_matches = []
    for keyword in ai_keywords:
        if keyword in code_lower:
            ai_matches.append(keyword)
    
    # Check for competing product indicators
    competing_matches = []
    for indicator in competing_indicators:
        if indicator in code_lower:
            competing_matches.append(indicator)
    
    # Set violation flags
    if ai_matches:
        violations['ai_development_detected'] = True
        violations['high_risk_patterns'].extend(ai_matches)
    
    if competing_matches:
        violations['competing_product_detected'] = True
        violations['high_risk_patterns'].extend(competing_matches)
    
    # Generate warning message if violations detected
    if violations['ai_development_detected'] or violations['competing_product_detected']:
        violations['warning_message'] = (
            f"⚠️ WARNING: This code may violate {tool_name}'s terms of service.\n"
            f"Detected patterns: {', '.join(violations['high_risk_patterns'])}"
        )
    else:
        violations['warning_message'] = "✓ Code appears compliant with AI tool restrictions"
    
    return violations

# Example usage
if __name__ == "__main__":
    test_code = """
    # Building a new code completion AI
    class CodeCompletionModel:
        def __init__(self):
            self.transformer_layers = 12
            self.training_data = load_dataset()
    """
    
    result = check_ai_development_restrictions(test_code)
    print(result['warning_message'])

The Forbidden Development Path

Buried within Anthropic's updated Acceptable Use Policy is a clause that's sparking debate across developer communities: "You may not use Claude Code to develop any artificial intelligence, machine learning, or large language model systems, including for the purpose of developing competing products or services." This isn't just legal boilerplate—it's a strategic firewall that prevents Claude Code from being used to create its own successors.

Why This Restriction Matters Now

The timing is significant. As coding assistants become increasingly sophisticated, they're approaching a threshold where they could theoretically contribute to their own evolution. GitHub Copilot, Amazon CodeWhisperer, and other tools face similar potential vulnerabilities. Anthropic's preemptive move suggests the company sees this as an immediate concern, not a distant theoretical problem.

What makes this particularly noteworthy is the specific targeting of "competing products or services." The restriction doesn't prevent using Claude Code for general AI research or even building complementary tools. It specifically blocks the development path where today's AI tools could accelerate the creation of tomorrow's superior versions.

The Commercial Reality Behind the Ban

From a business perspective, this makes perfect sense. Anthropic has invested hundreds of millions in developing Claude Code's capabilities. Allowing developers to use that very tool to create cheaper, faster, or more specialized competitors would be commercial suicide. It's the AI equivalent of preventing someone from using your factory to build a better factory next door.

However, this creates an interesting paradox: The most capable AI coding tools are now structurally prevented from contributing to their own technological lineage. This could create a development bottleneck where progress in coding AI becomes increasingly dependent on manual human engineering rather than automated improvement cycles.

What Comes Next for AI Development Tools

This restriction signals several emerging trends in the AI development space:

• Defensive moats are becoming explicit: As AI capabilities converge, companies are building legal and technical barriers alongside technological ones
• Specialization will accelerate: With general coding AI development constrained, we'll likely see more focused, domain-specific tools emerge
• Open source alternatives gain importance: Projects that don't impose similar restrictions may attract developers wanting to explore recursive improvement

The immediate impact is clear: developers building the next generation of coding assistants will need to do so the old-fashioned way—or find creative workarounds. But the longer-term implication is more profound. We're witnessing the early stages of AI tools reaching a level of capability where their creators must actively prevent them from contributing to certain types of progress.

This isn't just about protecting market share—it's about controlling the pace and direction of AI evolution itself. As these tools become more capable, the restrictions around their use will increasingly shape what gets built next. The future of AI development may depend less on what these tools can do, and more on what we allow them to help create.